Stock Market Returns and Direction Prediction: An Empirical Study on Karachi Stock Exchange

There has been much research in the recent past on the predictability of stock return, mainly due to its significance in managing economic gains on a high scale. Our research initiates the forecasting of the Karachi stock return with the help of the Wavelet analysis and Empirical mode decomposition method. This paper attends in large part to investors and traders to deduce a method for predicting the stock market. The collected data ranges from Jan 2009 to Dec 2012. Every training set is selected from January through October and the sets left over are used for testing. What we have discovered is that Empirical Mode decomposition (EMD) method supersedes all other models on the Mean square error and Mean Absolute error criteria. We may also evaluate the performance of these models by changing strategy direction and comparing payoffs to understand which framework performs as a better forecasting model. It is establishes by the results of the study that the same model serves better for forecasting in trading strategy and could rule over other possible models for most periods under consideration. It is our belief that this study will help stock investors to come to quick decisions about optimal buying or selling time in Karachi Stock Exchange Key Words: Forecasting, KSE (Karachi Stock Exchange) 100 Index, Empirical Mode Decomposition, Trading Strateg

MHD Stagnation-Point Flow of a Nanofluid with Heat and Mass Transfer in the Presence of Thermal Radiation

The steady two-dimensional magnetohydrodynamics stagnation point flow of a nanofluid with radiation effect is investigated. Using a similarity transformation, the governing partial differential equations are reduced to ordinary differential equations. The transformed equations are solved numerically for three types of nanoparticles, namely copper (Cu), alumina (Al2O3), and titania (TiO2) by using shooting method. The features of the flow with heat and mass transfer characteristics for different values of governing parameters are analyzed and discussed. Comparison with published results is presented and it found to be in good agreement. Key Words: Nanofluid, Heat and Mass Transfer, Thermal Radiation, Stagnation-Point Flo

Dual Beta Modeling of Karachi Stock Exchange

In the past three decades, the documentation of many features of returns in equity market has been noticed. But less attention has been paid to the feature attacks more commenting else, namely that there are extensive periods of time when equity prices rise and fall colloquially, these periods of time referred to as bull and bear markets respectively. The purpose of this research is to study the betas in the bull and bear market condition for a sample of stocks in the Karachi Stock Market (KSE), major stock market in Pakistan. The data consist of daily returns of two major sectors (Petroleum & Commercial banks) of KSE during the period of February 1997 to December 2007. The data pertains to the daily adjusted closing prices of 15 scripts that form a part of KSE index. This paper investigates whether betas of bull and bear market are statistically different from each other? KSE does not integrate any distribution so we use t-statistics.  Analysis shows that beta is higher when the market is bearish than that when market is bullish for nine stocks while the reverse is true for other six stocks. Keywords: Portfolio Beta, Portfolio Returns, KSE, Dual Bet

Forecasting Gold Price: Evidence from Pakistan Market

In our day to day life, predictability of gold’s prices is significant in many domains such as economics financial and political environment. The main objective of this research is to forecasts the prices of gold, making use of ARIMA and two distinct versions of wavelet scheme. The monthly data consists of 221 observations starting from Dec 2005 to April 2013, has been used in this research. After evaluating the accuracy of these models by mean absolute error and mean square error, it turns out that wavelet neural transformation has better prediction accuracy than rest of the models. Also, this study utilizes the return forecasts from the above mentioned different models in a simple trading strategy and compare pay offs in order to know as to which framework serves a better forecasting model. Keywords: Gold Price, ARIMA, Wavelet, Multiple Regression, Wavelet Neural Transform, Error Analysi

Numerical Solution of Airy Differential Equation by Using Haar Wavelet

Haar wavelet is exceedingly simple and optimized completely for computers, so that it can be used for solving ordinary differential equations and partial differential equations without a hassle. In this paper, numerical solutions of Airy differential equations have been obtained by using the Haar Wavelet Method . Comparisons with exact solutions make clear that the Haar Wavelet Method is a powerful candidate for solving the Airy differential equation. Moreover the use of Haar wavelets is found to be accurate, uncomplicated, speedy, adaptable and convenient with very small computation costs and the extra perk of being computationally attractive. Key Words: Orthogonal Wavelet, Airy Equation, Function Approximation, Operational Matri

Application of Elzaki Transform Method on Some Fractional Differential Equations

In the paper, we begin by introducing the origin of fractional calculus and the consequent application of the Elzaki transform on fractional derivatives. The Elzaki transformation may be used to solve mathematical problems without resorting to a new frequency domain. Once we establish this connection firmly in the general setting, we turn our attention to the application of the Elzaki transform method to some non-homogeneous fractional, ordinary differential equations. Ultimately, we acquire the graphical solution of the problem by using Matlab 2013a, developed by MathWorks Key Words: Elzaki Transform, Fractional Differential Equation, Linear and Non-linear, Initial Value Problem, Non-homogenou

A Hybrid Gold’s Returns Prediction Model Based on Empirical Mode Decomposition

Consumers have produced extraordinary levels of demand of Gold since the beginning of the financial crisis in 2008 and investment in small coins and bars striking a record high. Since the previous decade, the prices have reached the sky, but the demand for gold remains firm. With such an enormous need for gold coming from whole over the globe, forecast gold prices are of great interest. The main aim of this study is to forecast the price of gold returns, making use of Autoregressive (AR), Empirical Mode Decomposition Autoregressive (EMDAR) and hybrid Empirical Mode Decomposition Autoregressive Neural Network (EMDARNN). The daily data consists of 4837 observations starting from Jan 1995 to June 2013, has been used in this research. After assessing the accuracy of these models by mean absolute error and mean square error, it turns out that hybrid Empirical Mode Decomposition Autoregressive Neural Network excels all the other methods and produces better forecasting with high precision. Keywords: Gold Price, Autoregressive, Empirical Mode decomposition, Artificial Neural Networ

Humic acid from Shilajit – a physico-chemical and spectroscopic characterization

Shilajit is a blackish–brown exudation, consisting of organic substances, metal ions and minerals, from different formations, commonly found in the Himalayan region (1000–3000 m) from Nepal to Kashmir. Shilajit can also be collected throughout the mountain regions in Afghanistan, Bhutan, China, Bajkal, throughout Ural, Caucasus and Altai mountains also, at altitudes between 1000 to 5000 m. The major physiological action of shilajit has been attributed to the presence of bioactive dibenzo-α-pyrones together with humic and fulvic acids, which act as carrier molecules for the active ingredients. In this work, the aim was to extract humic acid from Shilajit from various sources and characterised these humic acids based on their physicochemical properties, elemental analysis, UV/Vis and FTIR spectra, X-ray diffraction pattern and DSC thermograms. The spectral features obtained from UV/Vis, FTIR, XRD and DSC studies for samples of different origins showed a distinct similarity amongst themselves and in comparison to soil humic acids. The surfactant properties of the extracted fulvic acids were investigated by determining the effect of increasing concentration on the surface tension of water. The study demonstrated that humic acids extracted from shilajit indeed possessed surfactant properties

Phytochemical, antimicrobial and cytotoxicity screening of ethanol extract of Acacia ehrenbergiana Hayne grown in Jazan Region of Saudi Arabia

Purpose: To explore the phytoconstituents of Acacia ehrenbergiana Hayne as well as its biological effects. Methods: Determination of phytoconstituents of ethanol extract of the plant was performed by gas chromatography-mass spectrometry (GC-MS) technique. Antibacterial screening was conducted against the isolates of Gram-positive and Gram-negative microbes while the anti-carcinogenic properties of the ethanol extract on cancerous cells were investigated by 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyl tetrazolium bromide (MTT) cytotoxicity assay against breast MCF7, ovary cancer A2780 and colon cancer HT29 cells, respectively, in addition to normal MRC5 fibroblast cells. Results: GC-MS analysis identified 15 different phytochemicals in the ethanol extract. The extract exerted significant antimicrobial activity with the minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) in the range 1.56 - 6.25 and 3.12 – 12.5 mg/L, respectively, against all test bacterial strains. Cytotoxic activity, obtained by MTT assay, was 28.81 ± 0.99, 12.50 ± 2.50, 23.90 ± 0.74 and 50.58 ± 3.24 μg/mL, against the three cancer cell lines and normal fibroblast, respectively. MTT cytotoxicity results was further confirmed by clonogenic survival assay on MCF7 cells. Conclusion: This study highlights the potential interesting ethnopharmacological applications of Acacia ehrenbergiana Hayne to treat drug-resistant pathogens as standardized extract. Keywords: Acacia ehrenbergiana, Phytochemistry, Antimicrobial, Cytotoxicit